IEEE transactions on neural networks and learning systems
Feb 28, 2022
Traditional neuron models use analog values for information representation and computation, while all-or-nothing spikes are employed in the spiking ones. With a more brain-like processing paradigm, spiking neurons are more promising for improvements ...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
Recent decades have witnessed a trend that control-theoretical techniques are widely leveraged in various areas, e.g., design and analysis of computational models. Computational methods can be modeled as a controller and searching the equilibrium poi...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
Text classification is a fundamental and important area of natural language processing for assigning a text into at least one predefined tag or category according to its content. Most of the advanced systems are either too simple to get high accuracy...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
This article presents an adaptive control method for dual-arm robot systems to perform bimanual tasks under modeling uncertainties. Different from the traditional symmetric bimanual robot control, we study the dual-arm robot control with relative mot...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
This brief is concerned with the stability of a neural network with a time-varying delay using the quadratic function negative-definiteness approach reported recently. A more general reciprocally convex combination inequality is taken to introduce so...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
Buildings constitute one of the most important landscapes in remote sensing (RS) images and have been broadly analyzed in a wide range of applications from urban planning to other socioeconomic studies. As very-high-resolution (VHR) RS imagery become...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
With wide deployment of deep neural network (DNN) classifiers, there is great potential for harm from adversarial learning attacks. Recently, a special type of data poisoning (DP) attack, known as a backdoor (or Trojan), was proposed. These attacks d...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
This article solves the problem of optimal synchronization, which is important but challenging for coupled fractional-order (FO) chaotic electromechanical devices composed of mechanical and electrical oscillators and electromagnetic filed by using a ...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
Deep neural networks are vulnerable to adversarial attacks. More importantly, some adversarial examples crafted against an ensemble of source models transfer to other target models and, thus, pose a security threat to black-box applications (when att...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
This article addresses the output feedback control of micromechanical (MEMS) gyroscopes using neural networks (NNs) and disturbance observer (DOB). For the unmeasured system states, the state observer and the high gain observer are constructed. The a...